Synthetic Aperture Radar (SAR) data for sea ice mapping

The prime source of information for operational sea ice services including the North American, the Finnish, the Norwegian and the Greenlandic ice service is satellite SAR data. These services represent the largest operational users of SAR data world wide. Completely automated mapping is not yet feasible but the manual interpretation is aided using automated classification and feature enhancement techniques.

The figure shows a Radarsat standard mode (100x100km) image from the Lincoln Sea May 15. 2004, classified into different ice types using a semi-automatic fuzzy-logic algorithm.
Yellow - multiyear ice; White - ridges; Red - first-year ice; Green - leads (new-ice)
040515_lincoln

Read more (pdf):
Gill, R. S., R. T. Tonboe. Classification of GreenIce SAR data using fuzzy screening method. In: Wadhams & Amanatidis (Eds.) Arctic Sea Ice Thickness: past, present and future. Climate change and natural hazards series 10, EUR 22416, 2007.

SAR image classification for validation

The use of thermal microwave data for mapping the sea ice extent and area is perhaps the most successfull application of satellite remote sensing for sea ice monitoring. Today time series covering the arctic regions daily from the early 1970s, are most significant for estimating inter-annual and decadal trends in this important climate parameter. The reduction over the past decades in the multiyear ice extent is an indication of an ongoing climate change process that affects the ice thickness as well. Even small changes in the sea ice concentration have a significant impact on energy fluxes between the ocean and the atmosphere, i.e. a change from 100% to 99% may double the fluxes. Once sea ice cover the ocean surface, the impact of ice thickness on heatflux is relatively small. From a climate change perspective, the key question is how fast the total volume of sea ice is changing. This requires reliable estimates of ice concentration for the derivation of the sea ice area. Therefore, ice concentration is an important ice cover parameter and must be estimated accurately. The Mean accuracy of some of the more common algorithms, used to compute ice concentration from radiometer data are reported to be 1-6 % in winter. These uncertainties are in general caused by atmospheric opacity, wind roughening of open water areas, sensor noise and anomalous ice surface emissivity.

The high resolution SAR data can be used to compare with the radiometer ice concentrations estimates.

The figure shows the neural network classification of a SAR image from Baffin Bay.
nnclassification

Read more (pdf):
S. Andersen, R. T. Tonboe, L. Kaleschke. Satellite thermal microwave sea ice concentration algorithm comparison. In: Wadhams & Amanatidis (Eds.) Arctic Sea Ice Thickness: past, present and future. Climate change and natural hazards series 10, EUR 22416, 2007.